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---
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Tr - CV 43h
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.1
type: mozilla-foundation/common_voice_16_1
config: tr
split: None
args: 'config: tr, split: test'
metrics:
- name: Wer
type: wer
value: 20.102435079521968
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small Tr - CV 43h
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2371
- Wer: 20.1024
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2134 | 0.37 | 500 | 0.2739 | 23.3965 |
| 0.1845 | 0.73 | 1000 | 0.2587 | 22.2823 |
| 0.1056 | 1.1 | 1500 | 0.2445 | 21.1214 |
| 0.1009 | 1.46 | 2000 | 0.2413 | 20.7278 |
| 0.0963 | 1.83 | 2500 | 0.2329 | 20.0952 |
| 0.0555 | 2.19 | 3000 | 0.2389 | 20.4421 |
| 0.0577 | 2.56 | 3500 | 0.2387 | 20.2588 |
| 0.0512 | 2.92 | 4000 | 0.2371 | 20.1024 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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